(1) Technical Field
The present invention relates to techniques for communications within distributed networks of sensor nodes. More specifically, the present invention relates to a technique for predicting the movement of an object through a network of sensor nodes.
(2) Discussion
Over the past several decades, the electronic communications field, particularly in the area of wireless communication, has exploded. As such, the abilities of small processing devices have increased considerably while the cost of these devices has decreased. Wireless communication generally takes place between specific devices or nodes. In order to perform tasks such as developing routes through a network, it is generally necessary to provide each member of a network with a unique identity so that specific devices can communicate. For example, in a cellular network or even in an ad-hoc network, a unique identity or address is assigned to each device so that it may exclusively receive calls targeted to its address. In addition, communications in most networks also require a “handshake” or mutual acknowledgement that a call or communication is to be set up. These networks depend on physical reliability in order function properly. Various communication properties are used in monitoring the performance of individual links in the network in order to adjust parameters of the communication system to maximize its effectiveness.
With the increased computational abilities and reduced cost of small, relatively simple devices comes the need for additional communication schemes that do not rely on the need for specific address assignments and complex communication acknowledgement schemes. It is desirable that these communication schemes take advantage of the processing capability of modem devices while conserving power by using local communications. More particularly, there exists a need in the art for a set of nodes (connected in either a wired or wireless fashion) that take advantage these local communication schemes in order to form a motion detection and prediction array.